Kazuhisa Shibata

Perceptual Learning Incepted by Decoded fMRI Neurofeedback Without Stimulus Presentation

Even the adult primary visual cortex is sufficiently plastic to allow performance enhancement. It is controversial whether the adult primate early visual cortex is sufficiently plastic to cause visual perceptual learning (VPL). The controversy occurs partially because most VPL studies have examined correlations between behavioral and neural activity changes rather than cause-and-effect relationships. With an online-feedback method that uses decoded functional magnetic resonance imaging (fMRI) signals, we induced activity patterns only in early visual cortex corresponding to an orientation without stimulus presentation or participants’ awareness of what was to be learned. The induced activation caused VPL specific to the orientation. These results suggest that early visual areas are so plastic that mere inductions of activity patterns are sufficient to cause VPL. This technique can induce plasticity in a highly selective manner, potentially leading to powerful training and rehabilitative protocols.

A small number of abnormal brain connections predicts adult autism spectrum disorder

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

Boosting perceptual learning by fake feedback

How does the brain control its sensory plasticity using performance feedback? We examined this question using various types of fake feedback in perceptual learning paradigm. We demonstrated that fake feedback indicating a larger performance improvement facilitated learning compared with genuine feedback. Variance of the fake feedback modulated learning as well, suggesting that feedback uncertainty can be internally evaluated. These results were explained by a computational model which controlled the learning rate of the visual system based on Bayesian estimation of performance gradient incorporating an optimistic bias. Our findings suggest that sensory plasticity might be controlled by high-level cognitive processes.

Resetting capacity limitations revealed by long-lasting elimination of attentional blink through training

As with other cognitive phenomena that are based upon the capacity limitations of visual processing, it is thought that attentional blink (AB) cannot be eliminated, even after extensive training. We report in this paper that just 1 h of specific attentional training can completely eliminate AB, and that this effect is robust enough to persist for a few months after training. Results of subsequent behavioral and functional magnetic resonance imaging (fMRI) experiments indicate that this learning effect is associated with improvements in temporal resolution, which are mainly due to processing in the prefrontal areas. Contrary to prior wisdom, we conclude that capacity limitations can be overcome by short-term training.

Decoding reveals plasticity in V3A as a result of motion perceptual learning.

Visual perceptual learning (VPL) is defined as visual performance improvement after visual experiences. VPL is often highly specific for a visual feature presented during training. Such specificity is observed in behavioral tuning function changes with the highest improvement centered on the trained feature and was originally thought to be evidence for changes in the early visual system associated with VPL. However, results of neurophysiological studies have been highly controversial concerning whether the plasticity underlying VPL occurs within the visual cortex. The controversy may be partially due to the lack of observation of neural tuning function changes in multiple visual areas in association with VPL. Here using human subjects we systematically compared behavioral tuning function changes after global motion detection training with decoded tuning function changes for 8 visual areas using pattern classification analysis on functional magnetic resonance imaging (fMRI) signals. We found that the behavioral tuning function changes were extremely highly correlated to decoded tuning function changes only in V3A, which is known to be highly responsive to global motion with human subjects. We conclude that VPL of a global motion detection task involves plasticity in a specific visual cortical area.

Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant

Overlearning refers to the continued training of a skill after performance improvement has plateaued. Whether overlearning is beneficial is a question in our daily lives that has never been clearly answered. Here we report a new important role: overlearning in humans abruptly changes neurochemical processing, to hyperstabilize and protect trained perceptual learning from subsequent new learning. Usually, learning immediately after training is so unstable that it can be disrupted by subsequent new learning until after passive stabilization occurs hours later. However, overlearning so rapidly and strongly stabilizes the learning state that it not only becomes resilient against, but also disrupts, subsequent new learning. Such hyperstabilization is associated with an abrupt shift from glutamate-dominant excitatory to GABA-dominant inhibitory processing in early visual areas. Hyperstabilization contrasts with passive and slower stabilization, which is associated with a mere reduction of excitatory dominance to baseline levels. Using hyperstabilization may lead to efficient learning paradigms.

Two‐stage model in perceptual learning: toward a unified theory

Training or exposure to a visual feature leads to a long‐term improvement in performance on visual tasks that employ this feature. Such performance improvements and the processes that govern them are called visual perceptual learning (VPL). As an ever greater volume of research accumulates in the field, we have reached a point where a unifying model of VPL should be sought. A new wave of research findings has exposed diverging results along three major directions in VPL: specificity versus generalization of VPL, lower versus higher brain locus of VPL, and task‐relevant versus task‐irrelevant VPL. In this review, we propose a new theoretical model that suggests the involvement of two different stages in VPL: a low‐level, stimulus‐driven stage, and a higher‐level stage dominated by task demands. If experimentally verified, this model would not only constructively unify the current divergent results in the VPL field, but would also lead to a significantly better understanding of visual plasticity, which may, in turn, lead to interventions to ameliorate diseases affecting vision and other pathological or age‐related visual and nonvisual declines.

Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure

Fear conditioning is a fundamentally important and preserved process across species1,2. In humans it is linked to fear-related disorders such as phobias and post-traumatic stress disorder (PTSD)3,4. Fear memories can be reduced by counter-conditioning, in which fear conditioned stimuli (CS+s) are repeatedly reinforced with reward5 or with novel non-threatening stimuli6. However, this procedure involves explicit presentations of CS+s, which is itself aversive before fear is successfully reduced. This aversiveness may be a problem when trying to translate such experimental paradigms into clinical settings7. It also raises the fundamental question as to whether explicit presentations of feared objects is necessary for fear reduction1,8. Although learning without explicit stimulus presentation has been previously demonstrated9–12, whether fear can be reduced while avoiding explicit exposure to CS+s remains largely unknown. One recently developed approach employs an implicit method to induce learning by reinforcing stimulus-specific neural representations using real-time decoding of multivariate functional magnetic resonance imaging (fMRI) signals13–15 in the absence of stimulus presentation; that is, pairing rewards with the occurrences of multi-voxel brain activity patterns matching a specific stimulus (decoded fMRI neurofeedback (DecNef)13,15). It has been shown that participants exhibit perceptual learning for a specific visual stimulus feature through DecNef, without being given any strategy for the induction of specific neural representations, and without awareness of the content of reinforced neural representations13. Here we examined whether a similar approach could be applied to counter-conditioning of fear. We show that we can reduce fear towards CS+s by pairing rewards with the activation patterns in visual cortex representing a CS+, while participants remain unaware of the content and purpose of the procedure. This procedure may be an initial step towards novel treatments for fear-related disorders such as phobia and PTSD, via unconscious processing.

Differential Activation Patterns in the Same Brain Region Led to Opposite Emotional States.

In human studies, how averaged activation in a brain region relates to human behavior has been extensively investigated. This approach has led to the finding that positive and negative facial preferences are represented by different brain regions. However, using a functional magnetic resonance imaging (fMRI) decoded neurofeedback (DecNef) method, we found that different patterns of neural activations within the cingulate cortex (CC) play roles in representing opposite directions of facial preference. In the present study, while neutrally preferred faces were presented, multi-voxel activation patterns in the CC that corresponded to higher (or lower) preference were repeatedly induced by fMRI DecNef. As a result, previously neutrally preferred faces became more (or less) preferred. We conclude that a different activation pattern in the CC, rather than averaged activation in a different area, represents and suffices to determine positive or negative facial preference. This new approach may reveal the importance of an activation pattern within a brain region in many cognitive functions.

Advances in fMRI Real-Time Neurofeedback

Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research.